Observed 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g \to q \bar{q}^{'} \tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm \to W^\pm \tilde{\chi}_2^0$ and $ \tilde{\chi}_2^0 \to Z \tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in signal region Rpc2L0b on the gluino and lightest neutralino masses in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Expected 95% CL exclusion contours in signal region Rpv2L on the gluino and lightest top squark masses in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Expected 95% CL exclusion contours in the best combination of signal regions of Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L0b, in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde \chi_1^\pm)$ = 1200 GeV, $m(\tilde \chi_2^0)$ = 1000 GeV and $m(\tilde \chi_1^0)$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L1b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 850 GeV, $m(\tilde \chi_1^\pm)$ = 500 GeV and $m(\tilde \chi_1^0)$ = 400 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc2L2b, in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$. The masses of the superpartners involved in the process are set to $m(\tilde{b}^{}_1)$ = 900 GeV, $m(\tilde \chi_1^\pm)$ = 150 GeV and $m(\tilde \chi_1^0)$ = 50 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpc3LSS1b, in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate. The masses of the superpartners involved in the process are set to $m(\tilde{t}^{}_1)$ = 800 GeV, $m(\tilde \chi_2^0)$ = 625 GeV, $m(\tilde \chi_1^\pm)\approx m(\tilde \chi_1^0)$ = 525 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Number of signal events expected for 139 fb$^{-1}$ at different stages of the event selection for the signal region Rpv2L, in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$. The masses of the superpartners involved in the process are set to $m(\tilde g)$ = 1600 GeV, $m(\tilde{t}^{}_{1})$ = 800 GeV. Only statistical uncertainties are shown.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal acceptance for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L0b signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L1b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpc2L2b signal region with sensitivity to $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpv2L signal region with sensitivity to $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Signal efficiency for Rpc3LSS1b signal region with sensitivity to $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into the lightest neutralino via a two-steps cascade, $\tilde g\to q\bar{q}^{'}\tilde{\chi}_1^\pm$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_2^0$ and $\tilde{\chi}_2^0\to Z\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde g\tilde g$ production cross-sections in a SUSY scenario where gluinos are produced in pairs and decay into a top quark and an top squark, which in turn decays via non-zero baryon-number-violating RPV couplings $\lambda^{''}_{313}$, $\tilde g\to t\tilde{t}_1$ followed by $\tilde{t}_1\to b d$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{b}^{}_1\tilde{b}^{*}_1$ production cross-sections in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Observed 95% CL upper limit on $pp\to \tilde{t}^{}_\mathrm{1}\tilde{t}^{*}_\mathrm{1}$ production cross-sections in a SUSY scenario where pairs of top-antitop squarks are produced and decay into the lightest neutralino via a two-steps cascade, $\tilde t^{}_{1}\to t\tilde{\chi}_2^0$ followed by $\tilde{\chi}_2^0\to \tilde{\chi}_1^\pm W^\mp$ and $\tilde{\chi}_1^\pm\to f\bar{f^{'}}\tilde{\chi}_1^0$. The lightest chargino and the lightest neutralino are assumed to be nearly mass-degenerate.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

Best observed 95% CL exclusion contours selected from Rpc2L1b and Rpc2L2b on the lightest bottom squark and lightest neutralino masses in a SUSY scenario where pairs of bottom-antibottom squarks are produced and decay into the lightest neutralino via a chargino, $\tilde b^{}_{1}\to t\tilde{\chi}_1^-$ followed by $\tilde{\chi}_1^\pm\to W^\pm\tilde{\chi}_1^0$.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L0b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}} / m_{\mathrm{eff}}$ of observed data and expected background towards Rpc2L1b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $E_{\mathrm{T}}^{\mathrm{miss}}$ of observed data and expected background towards Rpc2L2b from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

N-1 distributions for $m_{\mathrm{eff}}$ of observed data and expected background towards Rpv2L from publication's Figure 5 . The last bin is inclusive.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eleven jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with twelve-or-more jets in the different b-tag multiplicity bins for the 40 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 60 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with five jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with six jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with seven jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with eight jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with nine jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

The expected background and observed data with ten-or-more jets in the different b-tag multiplicity bins for the 80 GeV jet pT threshold. The background shown is estimated by including all bins in the fit.

Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Expected exclusion contours on the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Expected exclusion contours on the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Expected exclusion contours on the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Observed exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Expected exclusion contours on the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model where the gluino decays via a virtual top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino --> uds) via the RPV coupling lambda''_112.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed upper limits on the model cross-section in units of pb as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a third-generation quark and a higgsino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Observed upper limits on the model cross-section in units of pb as a function of the stop and neutralino masses in a model where the stop decays to a top and a bino-like neutralino, which decays via the RPV coupling lambda''_323.

Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Acceptance as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Efficiency as a function of the gluino and stop masses in a model where the gluino decays to a top quark and a top squark, with the top squark decaying to an s-quark and a b-quark via a non-zero lambda''_323 RPV coupling.

Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Acceptance as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Efficiency as a function of the gluino and neutralino masses in a model with a gluino decaying to two light quarks (q=u,d,s,c) and the neutralino, which then decays to two light quarks and a charged lepton or a neutrino.

Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where the gluino decays to two (u, d, s, c) quarks and the neutralino, which then decays to two (u, d, s, c) quarks and a lepton via a lambda' RPV coupling, where each RPV decay can produce any of the four first and second generation leptons (e, mu, nu_e, nu_mu) with equal probability (m_gluino = 1800 GeV, m_neutralino = 900 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays to a top quark and a top squark, with the top squark decaying to an s- and a b- quark via a non-zero lambda''_323 RPV coupling (m_gluino = 1600 GeV, m_stop = 1000 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of gluino pair production where each gluino decays via an off-shell top squark to two top quarks and the lightest neutralino, with the neutralino decaying to three light quarks (neutralino -> uds) via the RPV coupling lambda''_112 (m_gluino = 2000 GeV, m_neutralino = 941 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

Cut flow for a model of right-handed top squark pair production with the top squark decaying to the lightest supersymmetric particle (LSP) which is considered to be purely higgsino. The higgsino-like LSP decays through the non-zero RPV coupling lambda''_323 (m_stop = 975 GeV, m_neutralino = 600 GeV). The events are skimmed by requiring at least one electron or muon that satisfies very loose identification criteria, where the lepton satisfies pT > 25 GeV. The efficiency of this cut is considered in the quoted efficiency of the lepton trigger requirement. Selections with negligible inefficiencies on the given sample, such as data quality requirements, are not displayed.

<b>Kinematics 2</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SR&#8467;&#8467;-m_{&#8467;&#8467;} [1, 60] (top) and slepton SR&#8467;&#8467;-m_T2¹⁰⁰ [100, &infin;] (bottom) signal regions. The arrow in the E_T^miss/H_T^lep variables indicates the minimum value of the requirement imposed in the final SR selection. The m_{&#8467;&#8467;} and m_T2 distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H&#771; and slepton &#8467;&#771; simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 3</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SR&#8467;&#8467;-m_{&#8467;&#8467;} [1, 60] (top) and slepton SR&#8467;&#8467;-m_T2¹⁰⁰ [100, &infin;] (bottom) signal regions. The arrow in the E_T^miss/H_T^lep variables indicates the minimum value of the requirement imposed in the final SR selection. The m_{&#8467;&#8467;} and m_T2 distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H&#771; and slepton &#8467;&#771; simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 3</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SR&#8467;&#8467;-m_{&#8467;&#8467;} [1, 60] (top) and slepton SR&#8467;&#8467;-m_T2¹⁰⁰ [100, &infin;] (bottom) signal regions. The arrow in the E_T^miss/H_T^lep variables indicates the minimum value of the requirement imposed in the final SR selection. The m_{&#8467;&#8467;} and m_T2 distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H&#771; and slepton &#8467;&#771; simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 4</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SR&#8467;&#8467;-m_{&#8467;&#8467;} [1, 60] (top) and slepton SR&#8467;&#8467;-m_T2¹⁰⁰ [100, &infin;] (bottom) signal regions. The arrow in the E_T^miss/H_T^lep variables indicates the minimum value of the requirement imposed in the final SR selection. The m_{&#8467;&#8467;} and m_T2 distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H&#771; and slepton &#8467;&#771; simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 4</b> Kinematic distributions after the background-only fit showing the data as well as the expected background in the inclusive electroweakino SR&#8467;&#8467;-m_{&#8467;&#8467;} [1, 60] (top) and slepton SR&#8467;&#8467;-m_T2¹⁰⁰ [100, &infin;] (bottom) signal regions. The arrow in the E_T^miss/H_T^lep variables indicates the minimum value of the requirement imposed in the final SR selection. The m_{&#8467;&#8467;} and m_T2 distributions (right) have all the SR requirements applied. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The uncertainty bands plotted include all statistical and systematic uncertainties. The last bin includes overflow. The dashed lines represent benchmark signal samples corresponding to the Higgsino H&#771; and slepton &#8467;&#771; simplified models. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Exclusion 1 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 1 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 1 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 1 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 2 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 2 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 2 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 2 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with pm1&sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with pm1&sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct Higgsino (top) and wino (bottom) production. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive the limit, which is projected into the &Delta; m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) vs. m(&chi;&#771;₂⁰) plane. For Higgsino production, the chargino &chi;&#771;₁^pm mass is assumed to be halfway between the two lightest neutralino masses, while m(&chi;&#771;₂⁰) = m(&chi;&#771;₁^pm) is assumed for the wino--bino model. The gray regions denote the lower chargino mass limit from LEP [20]. The blue region in the lower plot indicates the limit from the 2&#8467;+3&#8467; combination of ATLAS Run 1 [41,42].

<b>Exclusion 3 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with &plusmn; 1 &sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with &plusmn; 1 &sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m_T2¹⁰⁰ spectrum is used to derive the limit, which is projected into the &Delta; m(&#8467;&#771;, &chi;&#771;₁⁰) vs. m(&#8467;&#771;) plane. Slepton &#8467;&#771; refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(e&#771;_L) = m(e&#771;_R) = m(&mu;&#771;_L) = m(&mu;&#771;_R). The gray region is the e&#771;_R limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].

<b>Exclusion 3 (exp)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with &plusmn; 1 &sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with &plusmn; 1 &sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m_T2¹⁰⁰ spectrum is used to derive the limit, which is projected into the &Delta; m(&#8467;&#771;, &chi;&#771;₁⁰) vs. m(&#8467;&#771;) plane. Slepton &#8467;&#771; refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(e&#771;_L) = m(e&#771;_R) = m(&mu;&#771;_L) = m(&mu;&#771;_R). The gray region is the e&#771;_R limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].

<b>Exclusion 3 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with &plusmn; 1 &sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with &plusmn; 1 &sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m_T2¹⁰⁰ spectrum is used to derive the limit, which is projected into the &Delta; m(&#8467;&#771;, &chi;&#771;₁⁰) vs. m(&#8467;&#771;) plane. Slepton &#8467;&#771; refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(e&#771;_L) = m(e&#771;_R) = m(&mu;&#771;_L) = m(&mu;&#771;_R). The gray region is the e&#771;_R limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].

<b>Exclusion 3 (obs)</b> Expected 95% CL exclusion sensitivity (blue dashed line) with &plusmn; 1 &sigma;_exp (yellow band) from experimental systematic uncertainties and observed limits (red solid line) with &plusmn; 1 &sigma;_theory (dotted red line) from signal cross-section uncertainties for simplified models of direct slepton production. A fit of slepton signals to the m_T2¹⁰⁰ spectrum is used to derive the limit, which is projected into the &Delta; m(&#8467;&#771;, &chi;&#771;₁⁰) vs. m(&#8467;&#771;) plane. Slepton &#8467;&#771; refers to the scalar partners of left- and right-handed electrons and muons, which are assumed to be fourfold mass degenerate m(e&#771;_L) = m(e&#771;_R) = m(&mu;&#771;_L) = m(&mu;&#771;_R). The gray region is the e&#771;_R limit from LEP [20,24], while the blue region is the fourfold mass degenerate slepton limit from ATLAS Run 1 [41].

<b>Upper Limits 1</b> The first two columns present observed (N_obs) and expected (N_exp) event yields in the inclusive signal regions. The latter are obtained by the background-only fit of the control regions, and the errors include both statistical and systematic uncertainties. The next two columns show the observed 95% CL upper limits on the visible cross-section (&lang;&epsilon;&sigma;&rang;_obs⁹⁵) and on the number of signal events (S_obs⁹⁵). The fifth column (S_exp⁹⁵) shows what the 95% CL upper limit on the number of signal events would be, given an observed number of events equal to the expected number (and +- 1 &sigma; deviations from the expectation) of background events. The last column indicates the discovery p-value (p(s = 0)), which is capped at 0.5.

<b>Upper Limits 1</b> The first two columns present observed (N_obs) and expected (N_exp) event yields in the inclusive signal regions. The latter are obtained by the background-only fit of the control regions, and the errors include both statistical and systematic uncertainties. The next two columns show the observed 95% CL upper limits on the visible cross-section (&lang;&epsilon;&sigma;&rang;_obs⁹⁵) and on the number of signal events (S_obs⁹⁵). The fifth column (S_exp⁹⁵) shows what the 95% CL upper limit on the number of signal events would be, given an observed number of events equal to the expected number (and +- 1 &sigma; deviations from the expectation) of background events. The last column indicates the discovery p-value (p(s = 0)), which is capped at 0.5.

<b>Cutflow 1</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.

<b>Cutflow 1</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.

<b>Acceptances 1</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 1</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 2</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 2</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 3</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 3</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 4</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 4</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 5</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 5</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 6</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 6</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 7</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 7</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^&plusmn; production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 8</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 8</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 9</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 9</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 10</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 10</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 11</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 11</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 12</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 12</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 13</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 13</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 14</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 14</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 15</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 15</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 16</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 16</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 17</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 17</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 18</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 18</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 19</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 19</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 20</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 20</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 21</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 21</b> Truth acceptances for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 22</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 22</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 23</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 23</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 24</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 24</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 25</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 25</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 26</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 26</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 27</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 27</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 28</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 28</b> Truth acceptances for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Numbers overlaid on the mass planes are the acceptance &times; 10⁴.

<b>Acceptances 29</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 29</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 30</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 30</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 31</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 31</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 32</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 32</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 33</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 33</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 34</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Acceptances 34</b> Truth acceptances for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Numbers overlaid on the mass planes are the acceptance &times; 10³.

<b>Efficiencies 1</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 1</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 2</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 2</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 3</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 3</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 4</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 4</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 5</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 5</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 6</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 6</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 7</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 7</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁺ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 8</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 8</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 9</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 9</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 10</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 10</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 11</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 11</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 12</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 12</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 13</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 13</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 14</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 14</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 15</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 15</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 16</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 16</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 17</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 17</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 18</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 18</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 19</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 19</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 20</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 20</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 21</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 21</b> Efficiencies for the Higgsino &chi;&#771;₂⁰&chi;&#771;₁⁰ production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 22</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 22</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 23</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 23</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 24</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 24</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 25</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 25</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 26</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 26</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 27</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 27</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 28</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 28</b> Efficiencies for the Higgsino &chi;&#771;₁⁺&chi;&#771;₁^- production process in the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 29</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 29</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 30</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 30</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 31</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 31</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 32</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 32</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 33</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 33</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 34</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Efficiencies 34</b> Efficiencies for the &#8467;&#771;&#8467;&#771; production in the inclusive SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Efficiencies are computed as the ``acceptance times efficiency" divided by the acceptance. The black line indicates the maximum allowed value of &Delta; m or m_T2 for the inclusive signal region under study.

<b>Cross-Sections 1</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 1</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 2</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 2</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 3</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 3</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 4</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 4</b> Cross-sections of the Higgsino signal grid for each production process denoted in the caption.

<b>Cross-Sections 5</b> Cross-sections of the wino--bino signal grid for each production process in the caption.

<b>Cross-Sections 5</b> Cross-sections of the wino--bino signal grid for each production process in the caption.

<b>Cross-Sections 6</b> Cross-sections of the wino--bino signal grid for each production process in the caption.

<b>Cross-Sections 6</b> Cross-sections of the wino--bino signal grid for each production process in the caption.

<b>Cross-Sections 7</b> Total cross-sections of the slepton simplified model signal grid. Slepton refers to a the scalar partners of the left- and right-handed electrons and muons, which are assumed to be mass degenerate m(e&#771;_L) = m(e&#771;_R) = m(&mu;&#771;_L) = m(&mu;&#771;_R).

<b>Cross-Sections 7</b> Total cross-sections of the slepton simplified model signal grid. Slepton refers to a the scalar partners of the left- and right-handed electrons and muons, which are assumed to be mass degenerate m(e&#771;_L) = m(e&#771;_R) = m(&mu;&#771;_L) = m(&mu;&#771;_R).

<b>Kinematics 5</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 5</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 6</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 6</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 7</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 7</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 8</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 8</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 9</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 9</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 10</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 10</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 11</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 11</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 12</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 12</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 13</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 13</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 14</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 14</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 15</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Kinematics 15</b> Distributions after the background-only fit of kinematic variables used to define selections common to all signal regions, i.e. not including requirements specific to the electroweakino or slepton SR definitions. Blue arrows in the upper panel denote the final requirement used to define the common SR, otherwise all selections are applied. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. The first (last) bin includes underflow (overflow). Benchmark Higgsino H&#771; and slepton &#8467;&#771; signals are overlaid as dashed lines. Orange arrows in the Data/SM panel indicate values that are beyond the y-axis range.

<b>Upper Limits 2</b> Numbers show 95% CL model-dependent upper limits on the inclusive Higgsino signal cross-sections.

<b>Upper Limits 2</b> Numbers show 95% CL model-dependent upper limits on the inclusive Higgsino signal cross-sections.

<b>Upper Limits 3</b> Numbers show 95% CL model-dependent upper limits on the inclusive Higgsino signal cross-sections.

<b>Upper Limits 3</b> Numbers show 95% CL model-dependent upper limits on the inclusive Higgsino signal cross-sections.

<b>Upper Limits 4</b> Numbers show 95% CL model-dependent upper limits on the inclusive signal cross-sections of the wino--bino model.

<b>Upper Limits 4</b> Numbers show 95% CL model-dependent upper limits on the inclusive signal cross-sections of the wino--bino model.

<b>Upper Limits 5</b> Numbers show 95% CL model-dependent upper limits on the inclusive signal cross-sections of the wino--bino model.

<b>Upper Limits 5</b> Numbers show 95% CL model-dependent upper limits on the inclusive signal cross-sections of the wino--bino model.

<b>Upper Limits 6</b> Numbers show the 95% CL model-dependent upper limits on the slepton signal cross-sections, assuming a fourfold mass degeneracy m(e&#771;_L,R) = m(&mu;&#771;_L,R).

<b>Upper Limits 6</b> Numbers show the 95% CL model-dependent upper limits on the slepton signal cross-sections, assuming a fourfold mass degeneracy m(e&#771;_L,R) = m(&mu;&#771;_L,R).

<b>Upper Limits 7</b> Numbers show the 95% CL model-dependent upper limits on the slepton signal cross-sections, assuming a fourfold mass degeneracy m(e&#771;_L,R) = m(&mu;&#771;_L,R).

<b>Upper Limits 7</b> Numbers show the 95% CL model-dependent upper limits on the slepton signal cross-sections, assuming a fourfold mass degeneracy m(e&#771;_L,R) = m(&mu;&#771;_L,R).

<b>Upper Limits 8</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m_1/2 for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the &plusmn; 1&sigma; and &plusmn; 2&sigma; uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the &chi;&#771;₂⁰ and &chi;&#771;₁⁰ masses for different values of m_1/2. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive this limit.

<b>Upper Limits 8</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m_1/2 for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the &plusmn; 1&sigma; and &plusmn; 2&sigma; uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the &chi;&#771;₂⁰ and &chi;&#771;₁⁰ masses for different values of m_1/2. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive this limit.

<b>Upper Limits 9</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m_1/2 for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the &plusmn; 1&sigma; and &plusmn; 2&sigma; uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the &chi;&#771;₂⁰ and &chi;&#771;₁⁰ masses for different values of m_1/2. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive this limit.

<b>Upper Limits 9</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m_1/2 for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the &plusmn; 1&sigma; and &plusmn; 2&sigma; uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the &chi;&#771;₂⁰ and &chi;&#771;₁⁰ masses for different values of m_1/2. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive this limit.

<b>Upper Limits 10</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m_1/2 for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the &plusmn; 1&sigma; and &plusmn; 2&sigma; uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the &chi;&#771;₂⁰ and &chi;&#771;₁⁰ masses for different values of m_1/2. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive this limit.

<b>Upper Limits 10</b> Expected and observed 95% CL cross-section upper limits as a function of the universal gaugino mass m_1/2 for the NUHM2 model. The gray numbers indicate the values of the observed limit. The green and yellow bands around the expected limit indicate the &plusmn; 1&sigma; and &plusmn; 2&sigma; uncertainties, respectively. The expected signal production cross-sections as well as the associated uncertainty are indicated with the blue solid and dashed lines. The lower x-axis indicates the difference between the &chi;&#771;₂⁰ and &chi;&#771;₁⁰ masses for different values of m_1/2. A fit of signals to the m_{&#8467;&#8467;} spectrum is used to derive this limit.

<b>Cutflow 2</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.

<b>Cutflow 2</b> Observed event yields and exclusion fit results with the signal strength parameter set to zero for the exclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.

<b>Cutflow 3</b> Observed event yields and background-only fit results for the inclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.

<b>Cutflow 3</b> Observed event yields and background-only fit results for the inclusive electroweakino and slepton signal regions. Background processes containing fewer than two prompt leptons are categorized as `Fake/nonprompt'. The category `Others' contains rare backgrounds from triboson, Higgs boson, and the remaining top-quark production processes listed in Table 1. Uncertainties in the fitted background estimates combine statistical and systematic uncertainties.

<b>Exclusion 4</b> Nominal observed and expected CLs values for Higgsino signals.

<b>Exclusion 4</b> Nominal observed and expected CLs values for Higgsino signals.

<b>Exclusion 5</b> Nominal observed and expected CLs values for wino--bino signals.

<b>Exclusion 5</b> Nominal observed and expected CLs values for wino--bino signals.

<b>Exclusion 6</b> Nominal observed and expected CLs values for slepton signals.

<b>Exclusion 6</b> Nominal observed and expected CLs values for slepton signals.

<b>Upper Limits 11</b> Upper limits on observed (expected) Higgsino simplified model signal cross section &sigma;_{obs (exp)}⁹⁵ and signal strength &sigma;_{obs (exp)}⁹⁵ / &sigma;_theory.

<b>Upper Limits 11</b> Upper limits on observed (expected) Higgsino simplified model signal cross section &sigma;_{obs (exp)}⁹⁵ and signal strength &sigma;_{obs (exp)}⁹⁵ / &sigma;_theory.

<b>Upper Limits 12</b> Upper limits on observed (expected) wino--bino simplified model signal cross section &sigma;_{obs (exp)}⁹⁵ and signal strength &sigma;_{obs (exp)}⁹⁵ / &sigma;_theory.

<b>Upper Limits 12</b> Upper limits on observed (expected) wino--bino simplified model signal cross section &sigma;_{obs (exp)}⁹⁵ and signal strength &sigma;_{obs (exp)}⁹⁵ / &sigma;_theory.

<b>Upper Limits 13</b> Upper limits on observed (expected) slepton simplified model signal cross section &sigma;_{obs (exp)}⁹⁵ and signal strength &sigma;_{obs (exp)}⁹⁵ / &sigma;_theory.

<b>Upper Limits 13</b> Upper limits on observed (expected) slepton simplified model signal cross section &sigma;_{obs (exp)}⁹⁵ and signal strength &sigma;_{obs (exp)}⁹⁵ / &sigma;_theory.

<b>Cutflow 4</b> Event counts for Higgsino H and slepton &#8467; signals after sequential selections for the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} and SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Weighted events are normalised to mathcalL = 36.1 fb^-1 and the inclusive cross section &sigma;, while raw MC events are also shown. The generator filter with efficiency &epsilon;_filt applied to the Higgsino signal requires truth E_T^miss &gt; 50 GeV and at least 2 leptons with p_T &gt; 3 GeV, while only the E_T^miss &gt; 50 GeV requirement is applied to the slepton signal. The mathcalB refers to the branching ratio Z^(*) &rarr; &#8467;⁺&#8467;^- in the Higgsino processes. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions.

<b>Cutflow 4</b> Event counts for Higgsino H and slepton &#8467; signals after sequential selections for the inclusive SR&#8467;&#8467;-m_{&#8467;&#8467;} and SR&#8467;&#8467;-m_T2¹⁰⁰ regions. Weighted events are normalised to mathcalL = 36.1 fb^-1 and the inclusive cross section &sigma;, while raw MC events are also shown. The generator filter with efficiency &epsilon;_filt applied to the Higgsino signal requires truth E_T^miss &gt; 50 GeV and at least 2 leptons with p_T &gt; 3 GeV, while only the E_T^miss &gt; 50 GeV requirement is applied to the slepton signal. The mathcalB refers to the branching ratio Z^(*) &rarr; &#8467;⁺&#8467;^- in the Higgsino processes. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions.

<b>Cutflow 5</b> Event counts for the &chi;&#771;₂⁰&chi;&#771;₁⁺ process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs), followed by those optimised for Higgsinos and sleptons. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 5</b> Event counts for the &chi;&#771;₂⁰&chi;&#771;₁⁺ process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs), followed by those optimised for Higgsinos and sleptons. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 6</b> Event counts for the &chi;&#771;₂⁰&chi;&#771;₁^- process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs), followed by those optimised for Higgsinos and sleptons. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 6</b> Event counts for the &chi;&#771;₂⁰&chi;&#771;₁^- process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs), followed by those optimised for Higgsinos and sleptons. ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 7</b> Event counts for the &chi;&#771;₂⁰&chi;&#771;₁⁰ process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement followed by those optimised for Higgsinos and sleptons. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 7</b> Event counts for the &chi;&#771;₂⁰&chi;&#771;₁⁰ process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement followed by those optimised for Higgsinos and sleptons. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 8</b> Event counts for the &chi;&#771;₁⁺&chi;&#771;₁^- process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs). ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

<b>Cutflow 8</b> Event counts for the &chi;&#771;₁⁺&chi;&#771;₁^- process of the Higgsino m(&chi;&#771;₂⁰, &chi;&#771;₁⁰) = (110, 100) GeV signal and sequentially with each addition requirement for selections common to all signal regions (SRs). ``Lepton truth matching" requires that the selected leptons are consistent with being decay products of the SUSY process. ``Lepton author 16 veto" removes a class of electron candidates reconstructed with algorithms designed to identify photon conversions. Weighted events are normalised to 36.1 fb^-1 and the raw Monte Carlo events are also displayed.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-onHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offLM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offMM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution is shown in the validation region VR-offHM after all the selection requirements are applied other than the $m_{CT}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. The red line with arrow indicates the $m_{CT}$ cut used in SR selection. The first and the last bin include the underflow and overflow events (where present), respectively.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-HM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-MM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{CT}$ distribution for SR-LM. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-HM after all the selection requirements are applied other than the $m_{bb}$ cut. The stacked histograms show the expected SM backgrounds. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection.The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-MM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The post-fit $m_{bb}$ distribution is shown in the signal region SR-LM after all the selection requirements are applied other than the $m_{bb}$ cut. The hatched bands represent the sum in quadrature of systematic and statistical uncertainties of the total SM background. For illustration, the distribution of the SUSY reference points are also shown as dashed lines. The red line with arrow indicates the $m_{bb}$ cut used in SR selection. The overflow events, where present, are included in the last bin.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion up limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The observed exclusion down limit for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. The red dotted lines indicate the $\pm 1 \sigma$ on the observed exclusion limit due to the theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

The expected exclusion for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. Experimental and theoretical systematic uncertainties are applied to background and signal samples and illustrated by the yellow band and the red dotted contour lines, respectively. The red dotted lines indicate the $\pm$ 1 standard-deviation variation on the observed exclusion limit due to theoretical uncertainties in the signal cross-section.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Upper limits on the cross sections for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production. 1lb\bar{b}$ production

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal acceptance in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-LM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-MM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM low $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM med. $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Signal efficiency in SR-HM high $m_{CT}$ for simplified models with $\tilde\chi^\pm_1 \tilde\chi^0_2 \rightarrow Wh\tilde\chi^0_1\tilde\chi^0_1, W \rightarrow l\nu, h \rightarrow b\bar{b}$ production.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-LM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-MM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM low $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM med. $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the SR-HM high $m_{CT}$. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-LM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-MM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Event selection cutflow for a representative signal sample for the discovery SR-HM. The masses of next-lightest-neutralinos and LSPs are reported. While the first row of the table reports the total raw MC events produced, all subsequent rows show weighted events. Only statistical uncertainties are shown. Samples are produced with generator filters which selects $h\rightarrow b\bar{b}$ and $W\rightarrow\ell\nu$ decays.

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{lead.~lep.}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 609 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $p_{\mathrm{T}}^{\mathrm{lead.~jet}}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 1485 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{lead.~jet}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{lead.~jet}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $H_{\mathrm{T}}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 2969 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $H_{\mathrm{T}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $S_{\mathrm{T}}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 3296 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $S_{\mathrm{T}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $m_{\mathrm{T},e\mu}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 4130 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{\mathrm{T},e\mu}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $m_{e\mu}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 3519 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $p_{\mathrm{T},e\mu}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 1067 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T},e\mu}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $\Delta\phi(e,\mu)$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\Delta\phi(e,\mu)$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\Delta\phi(e,\mu)$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $y_{e\mu}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $y_{e\mu}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $y_{e\mu}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $\cos\theta^*$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\cos\theta^*$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\cos\theta^*$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $n_{\mathrm{jet}}$. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $n_{\mathrm{jet}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $n_{\mathrm{jet}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $m_{e\mu}$ for $p_{\mathrm{T}}^{\mathrm{lead.~jet}} > 200$ GeV. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. Overflow events are included in the last bin. The largest observed value is 3519 GeV.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $m_{e\mu}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $\Delta\phi(e,\mu)$ for $p_{\mathrm{T}}^{\mathrm{lead.~jet}} > 200$ GeV. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\Delta\phi(e,\mu)$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\Delta\phi(e,\mu)$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $\Delta\phi(\mathrm{sub-lead.~lep.}, \mathrm{lead.~jet})$ for $p_{\mathrm{T}}^{\mathrm{lead.~lep.}} > 200$ GeV. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\Delta\phi(\mathrm{sub-lead.~lep.}, \mathrm{lead.~jet})$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\Delta\phi(\mathrm{sub-lead.~lep.}, \mathrm{lead.~jet})$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $\Delta R(\mathrm{sub-lead.~lep.}, \mathrm{lead.~jet})$ for $p_{\mathrm{T}}^{\mathrm{lead.~lep.}} > 200$ GeV. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $\Delta R(\mathrm{sub-lead.~lep.}, \mathrm{lead.~jet})$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $\Delta R(\mathrm{sub-lead.~lep.}, \mathrm{lead.~jet})$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}} / p_{\mathrm{T}}^{\mathrm{lead.~lep.}}$ for $p_{\mathrm{T}}^{\mathrm{lead.~lep.}} > 200$ GeV. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}} / p_{\mathrm{T}}^{\mathrm{lead.~lep.}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}} / p_{\mathrm{T}}^{\mathrm{lead.~lep.}}$

Measured fiducial cross section for $pp\rightarrow W^+W^-$+jets production for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}} / p_{\mathrm{T}}^{\mathrm{lead.~jet}}$ for $p_{\mathrm{T}}^{\mathrm{lead.~lep.}} > 200$ GeV. The second column contains the results obtained with a fiducial particle phase space that includes a veto on $b$-jets. This alternative result is obtained from the nominal result by the application of bin-wise correction that is calculated as the ratio of the predicted differential cross-section in the nominal analysis phase space and the predicted cross-section for a phase space that includes a veto on events with $b$-jets with $p_{\mathrm{T}} > 20$ GeV. Also shown are the Standard Model predictions for $q\bar{q} \rightarrow WW$, obtained from Sherpa 2.2.2, MadGraph 2.3.3 + Pythia 8.212 using FxFx merging, and Powheg MiNLO + Pythia 8.244. These predictions are supplemented by the Sherpa 2.2.2 + OpenLoops simulation of $gg\rightarrow WW$. Finally, the prediction from MATRIX is given, which includes nNLO QCD and NLO EW corrections to $WW$+jet production. The largest observed value is 19.6.

Correlation matrix of the statistical uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}} / p_{\mathrm{T}}^{\mathrm{lead.~jet}}$

Correlation matrix of the total uncertainties in the measured fiducial cross section for the observable $p_{\mathrm{T}}^{\mathrm{sub-lead.~lep.}} / p_{\mathrm{T}}^{\mathrm{lead.~jet}}$

The +1 $\sigma$ band of the observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the $Z^{\prime}_{B}$ model in the $m_{\chi}$-$m_{Z^{\prime}_{B}}$ plane.

A comparison of the inferred limits to the constraints from direct detection experiments on the spin-independent DM--nucleon cross section in the context of the $Z'_B$ simplified model with vector couplings. Limits are shown at 90% CL.

The observed exclusion contor for the $Z^{\prime}$-2HDM model in the $m_{A}$-$m_{Z^{\prime}}$ plane.

The expected exclusion contor for the $Z^{\prime}$-2HDM model in the $m_{A}$-$m_{Z^{\prime}}$ plane.

The +1 $\sigma$ band of the observed exclusion contor for the $m_{A}$-$Z^{\prime}$-2HDM model in the $m_{Z^{\prime}}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the $m_{A}$-$Z^{\prime}$-2HDM model in the $m_{Z^{\prime}}$ plane.

The observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The expected exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The +1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $m_{A}$-$m_{a}$ plane.

The observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The expected exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The +1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The -1 $\sigma$ band of the observed exclusion contor for the 2HDM-a model in the $tan\beta$-$m_{a}$ plane.

The exclusion limits at 95% CL for the 2HDM+a model as a function of $\sin \theta$ for $m_{A,H^{\pm},H}$= 600GeV, $m_a$ = 200GeV, $\tan \beta$ = 1.0$.

The exclusion limits at 95% CL for the 2HDM+a model as a function of $\sin \theta$ for $m_{A,H^{\pm},H}$= 1000GeV, $m_a$ = 350GeV, $\tan \beta$ = 1.0$.

Breakdown of the dominant systematic uncertainties.

Event yields in the range of 120 $<m_{\gamma\gamma}<$ 130 GeV for data, signal models, the SM Higgs boson background and non-resonant background in each analysis category, for an integrated luminosity of $139$fb$^{-1}$.

Detailed background contributions from the SM Higgs boson and continuum background for each cut

Detailed contributions from the signals for each cut.

Acceptance times efficiency for several signals in each category.

Acceptances on TRUTH level of the DMt samples in the tW1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Efficiencies of the DMt samples in the tW2L SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Acceptances on TRUTH level of the DMt samples in the tW2L SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Efficiencies of the DMt samples in the tj1L channel for all bins in the SR. The efficiency is defined as the number of weighted reconstructed events over the number of weighted TRUTH events in the SR. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Acceptances on TRUTH level of the DMt samples in the tj1L channel for all bins in the SR. The acceptance is defined as the number of weighted TRUTH events in the SR over the number of expected events without any selections. The map includes all used samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW1L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering only DMt signal.

Upper limits on excluded cross sections of the tW2L analysis considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.

Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering only the DMt signal.

Upper limits on excluded cross sections of the combined tW1L and tW2L analyses considering only the DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming only $tW$+DM contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW1L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW1L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tW2L analysis considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_a, m_{H^{\pm}})$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the combined tW1L and tW2L analyses considering the DMt$\bar{t}$+DMt signal.

The expected exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

The observed exclusion contours as a function of $(m_{H^{\pm}}, \tan\beta)$, assuming DM$t\bar{t}$ and DM$t$ contributions, for the statistical combination of the tW1L and tW2L analysis channel.

Upper limits on signal strength (excluded cross section over theoretical cross section) of the tj1L analysis considering only the DMt signal.

Upper limits on upper limits on excluded cross sections of the tj1L analysis considering only the DMt signal.

The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.3$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.

The expected and observed cross section exclusion limits as a function of $m_{H^{\pm}}$ in the tj1L analysis channel for signal models with $m_a = 250~GeV$, and $\tan\beta=0.5$. The $\sigma^{}_\mathrm{BSM}$ is the cross section of the $t$-channel DM production process.

Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Cross sections of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

Cross sections times branching ratio of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Cross sections of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

MC generator filter efficiencies of the DMt samples in the tW1L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_a - m_H$ plane with $tan\beta = 1$.

MC generator filter efficiencies of the DMt samples in the tW2L channel. The maps include all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

MC generator filter efficiencies of the DMt samples in the tj1L channel. The map includes all samples in the $m_H - tan\beta$ plane with $m_a = 250~GeV$.

Background-only fit results for the tW1L and tW2L signal regions. The backgrounds which contribute only a small amount (rare processes such as triboson, Higgs boson production processes, $t\bar{t}t\bar{t}$, $t\bar{t}WW$ and non-prompt or misidentified leptons background) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.

Background-only fit results for the tj1L signal regions. The backgrounds which contribute only a small amount ($Z$+jets, rare processes such as $tWZ$, triboson, Higgs boson production processes, ,$t\bar{t}t\bar{t}$, $t\bar{t}WW$) are grouped and labelled as ``Others´´. The quoted uncertainties on the fitted SM background include both the statistical and systematic uncertainties.

Cutflow of the weighted events with statistical uncertainties for two DMt samples in all bins of the tW1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Cutflow of the weighted events with statistical uncertainties for two DMt samples in the tW2L channel. The PreSelection includes at least 2 leptons in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 40~GeV$, $m_{ll} > 40~GeV$, $m\mathrm{_{T2}} > 40~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

Cutflow of the weighted events with the statistical uncertainties (except for the first cuts) for two DMt samples in all bins off the tj1L channel. The PreSelection includes at least 1 lepton in the event, at least 1 $b$-jet with $p_{\mathrm{T}} > 50~GeV$, $m\mathrm{_{T}^{lep}} > 30~GeV$, $\Delta\phi\mathrm{_{4jets, MET}^{min}} > 0.5$ and $E\mathrm{_{T}^{miss}} > 200~GeV$.

The \(m_{bb}\) distributions in the MediumBDT categories, overlaid with contributions from the \(H\gamma jj\) signal as well as the resonant \(Z\gamma jj\) and non-resonant \(b\bar{b} \gamma jj\) background fits. The combined \(\chi^2\) per degree of freedom is \(45.2/45\). The bottom panel in each plot presents the significance of the Higgs boson signal relative to the non-resonant \(b\bar{b} \gamma jj\) background in each bin.

The \(m_{bb}\) distributions in the MediumBDT categories, overlaid with contributions from the \(H\gamma jj\) signal as well as the resonant \(Z\gamma jj\) and non-resonant \(b\bar{b} \gamma jj\) background fits. The combined \(\chi^2\) per degree of freedom is \(45.2/45\). The bottom panel in each plot presents the significance of the Higgs boson signal relative to the non-resonant \(b\bar{b} \gamma jj\) background in each bin.

Comparisons of data and simulated event distributions of the BDT input variables \(\Delta R (b1, \gamma)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(m_{jj}\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(\Delta R (b2, \gamma)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(\text{centrality}(\gamma, j1, j2)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(\Delta \phi(b\bar{b}, jj)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(p_{\mathrm{T}}^{jj}\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(\cos \theta\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Comparisons of data and simulated event distributions of the BDT input variables \(\Delta R(b1,j1)\) in the two \(m_{bb}\) sidebands after kinematic reweighting of the non-resonant \(b\bar{b}\gamma jj\) background. The data are shown as black points, and the background contributions are stacked in coloured histograms. The Higgs boson signal contribution is scaled up and represented by the dashed red line. The bottom panel in each plot shows the ratio between the data and the SM prediction, where the uncertainty band corresponds to the statistical uncertainty only.

Observed and expected limits on $\tan\beta$ as a function of $m_{H^+}$ in the $M_h^{125}(\tilde{\chi})$ scenario. Limits are shown for $\tan\beta$ values in the range of 0.5-60 due to the availability of the model prediction. The bands surrounding the expected limits show the 68% and 95% confidence intervals. Uncertainties in the predicted $H^+$ cross-sections or branching ratios are not considered.

Observed and expected limits on $\tan\beta$ as a function of $m_{H^+}$ in the $M_h^{125}(\tilde{\tau})$ scenario. Limits are shown for $\tan\beta$ values in the range of 0.5-60 due to the availability of the model prediction. The bands surrounding the expected limits show the 68% and 95% confidence intervals. Uncertainties in the predicted $H^+$ cross-sections or branching ratios are not considered.

Observed and expected limits on $\tan\beta$ as a function of $m_{H^+}$ in the $M_h^{125}$(alignment) scenario. Limits are shown for $\tan\beta$ values in the range of 0.5-60 due to the availability of the model prediction. The bands surrounding the expected limits show the 68% and 95% confidence intervals. Uncertainties in the predicted $H^+$ cross-sections or branching ratios are not considered.

Observed and expected limits on $\tan\beta$ as a function of $m_{H^+}$ in the $M_{h_1}^{125}$(CPV) scenario. Limits are shown for $\tan\beta$ values in the range of 0.5-60 due to the availability of the model prediction. The bands surrounding the expected limits show the 68% and 95% confidence intervals. Uncertainties in the predicted $H^+$ cross-sections or branching ratios are not considered.

Event yields of the SM background processes and the 800 GeV $H^{+}$ sample in the four analysis regions before the fit to the data. Uncertainties include both statistical and systematic uncertainties. The yields of the $H^{+}$ signal sample correspond to a cross-section times branching fraction of 10 pb.

Event acceptance for the different $H^+$ mass signal samples.

Efficiency in the Single-bin SR as a function of the M(Sbottom) vs. M(N2) with the $\Delta$ M(N2,N1) $= 130$ GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Acceptance in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.

Efficiency in the Multi-bin SR, $\min_{\Theta} < 0.5$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Acceptance in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.

Efficiency in the Multi-bin SR, $0.5 < \min_{\Theta} < 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Acceptance in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the acceptance is given in units of $10^{-4}$.

Efficiency in the Multi-bin SR, $\min_{\Theta} > 1.0$ bin as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV. Keep in mind that the efficiency is given in units of $10^{-2}$.

Observed upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.

Expected upper limits on the signal cross section as a function of the M(Sbottom) vs. M(N2) with the $\Delta M$(N2,N1) = 130 GeV.

Cutflows for the bechmarl signal point M(Sbottom) = 800 GeV, M(N2) = 180 GeV. Weighted event yields are reported starting with the "Preselection" line, normalized to an integrated luminosity of $139$ fb$^{−1}$.

Comparison of the expected and observed event yields in the signal regions. The top-quark and Z(mumu) background contributions are scaled with the normalization factors obtained from the background-only fit. The other contribution includes all the backgrounds not explicitly listed in the legend (V+jets except Z(mumu)+jets, di-/triboson, multijet). The hatched band indicates the total statistical and systematic uncertainties in the SM background. The contributions from three signal models to the signal regions are also displayed, where the masses M(Sbottom) and M(N2) are given in GeV in the legend. The lower panel shows the significance of the deviation of the observed yield from the expected background yield.

Dominant systematic uncertainties in the background prediction for the signal regions after the fit to the control regions. “Other” includes the uncertainties arising from muons, jet-vertex tagging, modeling of pile-up, the $E_{T}^{miss}$ computation, multijet background, and luminosity. The individual uncertainties can be correlated and do not necessarily add up quadratically to the total uncertainty.